Evaluation of an open-source nutrient delivery model for estimating pesticide loads in river catchments
Year: 2025
Type: article
Abstract: Diffuse source pesticide pollution is an issue for soils, wildlife, water quality, and human health. Quantifying the risk of catchments to pesticide runoff is, therefore, important for predicting these impacts and targeting mitigation. Achieving this at scale through long-term regular water quality monitoring at multiple sites is time- and resource-intensive. Ideally, such monitoring would be supplemented by models that can estimate pesticide loads in a quicker, less costly manner, especially for ungauged catchments. However, many existing models are complex to parametrise or do not produce spatially explicit outputs. In this study, we developed a novel modelling method combining the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Nutrient Delivery Ratio model and the UKCEH Land Cover® plus: Pesticides maps to model pesticide loads across southern Great Britain (GB). We compared our modelled approach for two pesticides of particular concern to the UK water industry, bentazone and chlorotoluron, with a measurement-based (“measured”) approach. For the latter, we used pesticide concentration data from the Environment Agency’s Water Quality Archive and generated influenced river flow data using Qube (an online water resource estimation tool) for catchments upstream of the monitoring sites. We identified 54 suitable catchments for bentazone and 21 for chlorotoluron. We found significant positive relationships between the measured and modelled pesticide loads. This relationship was stronger when the measured approach accounted for the proportionate area of arable land cover, emphasising that only pesticides from arable sources were incorporated in the modelled approach. Although the models did not produce a 1:1 relationship in terms of catchment load values, they explained up to 90 % of the variation in estimating relative risk between catchments. Thus, our model forms a flexible approach to mapping the relative risk of pesticide runoff over large spatial extents, especially for catchments or pesticides with limited monitoring.
Institutions: UK Centre for Ecology & Hydrology, HR Wallingford
Language: English
Subfield: Pollution
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,250
OpenAlex ID: W4408979758